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AMA, Agricultural Mechanization in Asia, Africa and Latin America

AMA, Agricultural Mechanization in Asia, Africa and Latin America (AMA) (issn: 00845841) is a peer reviewed journal first published online after indexing scopus in 1982. AMA is published by Farm Machinery Industrial Research Corp and Shin-Norinsha Co. AMA publishes every subjects of general engineering and agricultural engineering. Lizi Jiaohuan Yu Xifu/Ion Exchange and Adsorption Fa yi xue za zhi Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology Research Journal of Chemistry and Environment

Submission Deadline
26 Jun 2024 (Vol - 55 , Issue- 06 )
Upcoming Publication
30 Jun 2024 (Vol - 55 , Issue 06 )

Aim and Scope :

AMA, Agricultural Mechanization in Asia, Africa and Latin America

AMA, Agricultural Mechanization in Asia, Africa and Latin America (ISSN: 00845841) is a peer-reviewed journal. The journal covers Agricultural and Biological Sciences and all sort of engineering topic. the journal's scopes are in the following fields but not limited to:

Agricultural and Biological Sciences
Electrical Engineering and Telecommunication
Electronic Engineering
Computer Science & Engineering
Civil and architectural engineering
Mechanical and Materials Engineering
Transportation Engineering
Industrial Engineering
Industrial and Commercial Design
Information Engineering
Chemical Engineering
Food Engineering

Quality Protein Maize Hybrids (Zea mays L.) response on Growth parameters under Different Plant Populations and Nutrient Management Practices

Paper ID- AMA-22-02-2022-11157

A field experiment was conducted at Udaipur during Kharif season of 2016 to study the Response of Quality Protein Maize Hybrids (Zea mays L.) on Growth parameters under Different Plant Population and Nutrient Management Practices. Results revealed that hybrid HQPM-5 recorded higher plant population, plant height, dry matter accumulation at 25, 50 75 DAS and at harvest (19.70, 60.94, 197.51 and 214.47 g plant-1), CGR between 25-50 DAS (15.00 g m-2 day-1) and 50-75 DAS (50.07 g m-2 day-1), RGR, LAI over PQMH-1. Maize hybrid HQPM-5 attend significantly early tasseling and silking than PQMH-1. 1,00,000 plants ha-1 recorded higher DMA, CGR, RGR, LAI over 83,333 plants ha-1. Among various nutrient management practices STCR recorded highest plant height, DMA, CGR, RGR, LAI over SSNM and RDF, respectively.

Enhanced Flower Pollination Algorithm for Edge Detection and its Application for Segmentation of Banana Leaf Disease Image

Paper ID- AMA-21-02-2022-11155

Edge detection algorithms play a vital role in image processing, computer vision, and machine vision. There is a huge demand for efficient edge detection algorithms for identifying the exact region of interest in an image. The nature-inspired metaheuristic algorithms are more promising than traditional algorithms owing to their stochastic characteristics. The concept of the Flower Pollination Algorithm (FPA) has recently gained much attraction due to solving several complicated optimization problems. In this study, an efficient edge detection algorithm has been developed using FPA for identifying edges in an image. The proposed FPA is capable of identifying the edges with minimal parameterized values, and the parameters are initialized automatically using the concept of maximum entropy and polynomial curve fitting distribution. The performance of flower pollination based edge detection algorithm on ground truth images was compared with other existing methods like Sobel, Canny, Ant Colony based edge detection method, PSO method, and fuzzy-genetic based edge detection methods using Receiver Operating Characteristics (ROC) curve and Area Under Curve (AUC) method. The proposed method performed better compared with other existing methods and had significantly high ROC and AUC indices. Also, the performance of the proposed algorithm was tested on real-time banana leaf disease images and compared with other existing methods in terms of the Shannon entropy index. The segmented images of banana leaf disease through enhanced FPA showed significantly lower mean entropy value, indicating extra-ordinary accuracy and negligible uncertainty of the enhanced FPA. The proposed FPA seems to be promising in developing image processing modules for crop disease diagnosis.

Optimization of Nitrogen Level Under Integrated Weed Management Options for Higher Onion Productivity in Semi-arid Conditions

Paper ID- AMA-20-02-2022-11151

The present study was undertaken to understand the effects of nitrogen (N) on crop–weed interactions for development of integrated weed management (IWM) systems in onion. The field experiment was conducted in semi-arid conditions at SKN Agriculture University, Jobner (India). Seven IWM practices were tested in main plots and four N doses (0, 50, 100, and 150 kg ha-1) in sub plots. The experiment was laid out in split plot design with three replications using onion cultivar RO 252 during two 2016-17 and 2017-18. It was observed that the interactive use of N doses with IWM practices significantly affected crop dry matter (CDM) and marketable yield. Application of two hand weeding (HW) at 20 and 40 DAT combined with 120 kg Nha-1 was most effective to obtain higher marketable bulb yield of onion followed by pendimethalin (1.0 kg a.i. ha-1) + one HW at 40 DAT in combination with 120 kg Nha-1. The study will be useful to effectively control major weed flora and optimization of nitrogen dose for higher productivity of winter season onion crop in loamy sand soils of semi-arid conditions.

Energetics of different cropping systems as affected by resource conservation practices under sub-tropical conditions of Jammu Region

Paper ID- AMA-20-02-2022-11149

A field study was conducted (2012-14) on “energetics of different cropping systems under resource conservation practices” at the research farm, FSR, Centre, Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Main Campus, Chatha, Jammu, India. The experiment was laid out in split-plot design with two crop establishment methods (Minimum/Zero tillage and conventional tillage) and three cropping systems (Rice-Wheat, Rice-Marigold-French bean and Maize + soybean -Wheat) and two fertilizer rates (Rec. Dose of Fertilizer and 75% RDF + 25% N through FYM) with and without mulching in sub-plots under clay loam soil having alkaline in reaction (pH-8.1), medium in soil organic carbon (0.55%) available P (19.20 Kg ha-1 & K(122.0 Kg ha-1) and low in available N (221.12 Kg ha-1) with three replication The maximum input energy (105241 MJ) was recorded under mulched treatment and the maximum EUE was recorded 7.69 % and 7.01 % under maize + soybean - wheat cropping system followed by rice-wheat cropping system (7.49 % and 6.87 %) during first and second year of experimentation, respectively.

Rice threshing and separation process based on detachment force property of rice ears

Paper ID- AMA-20-02-2022-11148

The movement characteristics of rice are important indicators to explore the optimal threshing area and threshing force. This paper presents the motion parameters for threshing straw in the tangential and axial threshing units of the combine. Through the study of the optimal threshing area and threshing force, the reasons for the non-threshing of grains were obtained, which provided the basis for the design of the longitudinal and axial threshing drum. By comparing the threshing force and the detachment force of the grain stem, stem branch and branch axis, the threshing ability of each part of the longitudinal and axial threshing drum was obtained. The results showed that the separation force ranged from 1.48N to 2.29N. The straw performs approximately periodic helical motion in the axial threshing device. The grains on the ears are threshed by the ears of 1-6 rows of longitudinal and axial threshing drums. 2-3 rows of beaters produce stalked grains, and the optimum threshing force is 2.06 N-2.15 N to ensure threshing without stalks and branches. The research is of great significance to explore the optimal threshing zone and threshing parameters.